Medical supply management needs to make several valuable changes to optimize its processes. For example, creating a centralized monitoring system for routing supplies can assist with overall quality control and help meet demand quicker. Another beneficial way to improve supply chain management is incorporating effective technology.
Control centers with machine learning and blockchain technology can produce accurate reports of medical inventory and predict possible surges for medical supplies. However, it’s important to note that the consequences of delaying these changes can be severe, such as black-market medicine making its way into hospitals. Learn about the helpful improvements and valuable technology that can increase supply chain management efficiency.
A little over three years ago, I posted a blog about my then-new Tesla and my wife’s then-new Japanese car. The view I expressed was that the Tesla was conceived as an extensible software platform that happens to power a car, where my wife’s Japanese car was clearly conceived of as, well, a car. In other words, the Tesla is a platform, while my wife’s car is a “point solution.” I asserted that, over time, the Tesla would continue "growing" and adding new features, while my wife’s car would stay the same. Three years later, did that turn out to be the case? I can say, emphatically, that this has been the case.
Continuous Evolution, Continuous Delight
The Tesla has continued to evolve and delight me. While my wife’s car has been good, reliable, and comfortable transportation, it still does precisely what it did when she bought it four years ago, and does it in the same way. The Tesla, among many other new features, now literally drives itself, requiring only a destination to take me where I want to go. It stops and then goes again at stop lights and stop signs, watches out for pedestrians, bicyclists and motorcyclists, changes directions and navigates by itself, and brings me home—or wherever I want to go—without my involvement at all. Of course I am cautioned to stay alert and to override any unintended or dangerous behavior, but I have the feeling that’s as much out of corporate liability concerns as any other motivation.
While Tesla’s full, autonomous driving mode is in “beta” and does have some eccentricities IMO, I can testify that it’s real and it’s here today. And—more importantly in the context of my earlier blog—it’s now a feature of the same car that I bought three years ago. Three years ago, the Tesla had great low-speed follow and lane-keeping features, but nothing like what it can do today. In addition to “full self-driving” capability, my Tesla has spawned a host of new features over the last three years, ranging from a “theater mode” to new infotainment options, to UI changes, to more efficient energy recovery on braking. Since the whole car is software-controlled, basically any feature of the car and its performance can be optimized or enhanced.
Soft vs. Hard Controls
I have received at least 86 over-the-air software updates since 2019, nearly all of which added new features or enhancements. These were easy to apply—automatic, if you select that option. My wife’s Japanese car has had 6 firmware updates offered in the same time, mainly to fix defects. While her updates were nominally available over the air, doing so was so complex that in practice we either visited the dealer or downloaded software onto a dongle. OTA only started to work for us with the last of the six updates — I assume as the result of a previous fix.
Part of the reason the Tesla can be so flexible in terms of adding new features is that (a) the car itself is software controlled with minimal mechanical features, and (b) the vast majority of its controls are “soft” / touchscreen based. This means that the controls can be easily repurposed and reconfigured in software. Aside from the door locks, window controls and seat arrangement buttons, the Tesla only has seven mechanical controls: 2 thumbwheels, 2 rocker switches, and 3 levers (which have extra controls on them). All other controls are “soft.”
This “soft” nature of the Tesla’s controls is typical of the "abstract" nature of a platform architecture. A good platform is implemented at a degree of “abstraction” that allows components to pivot toward adjacent features. In the UI, this means making things like buttons “soft” so the "screen real estate" can be repurposed. In a server-side software platform, analogously, you seek to choose a level of abstraction that is high enough (but not too high) to enable pivots.
For example, in a banking application, one of the fundamental entities might be an “account” rather than a “checking account.” This would enable the same abstraction to deal with multiple types of accounts (e.g., checking, savings, investment) for those behaviors they have in common. The trick is making the abstraction concrete enough that it is intuitively obvious what it means, while at the same time general enough to allow for flexibility.
The Tesla UI has performed this trick through voluntary restraint. For example, while clearly they could put any controls anywhere on the touchscreen, they have kept the heating and infotainment controls in more-or-less the same position. Their function remains intuitive to the user, even though the features themselves have been generalized or changed. The "abstraction" remains similar.
Platform vs. Purpose-Built
My wife recently bought a new car; this time, one of Germany’s finest. Her 3-year-old Japanese car still works, but it no longer feels very exciting to her. Her new German car is indeed very cool—it has amazing laser-driven adaptive headlights, a first-rate heads-up display, good adaptive cruise control, a touchscreen with a gestural interface, and many other features. It’s clearly designed as a “driver’s car,” not as a self-driving one. The design goal is clearly around empowering the driver, not taking tasks off the driver’s shoulders. In spirit, her new car is very similar to her Japanese car—it’s clearly a car, not a platform.
Part of the “point solution” nature of my wife’s new car is evident from the number of dedicated mechanical controls. If I counted correctly, the dashboard, console and steering wheel of her new car have: 59 labeled mechanical buttons, 3 paddles, 1 joystick, 1 shift / gear control, 2 levers (with additional controls), 3 thumbwheels and a touch screen. The advantage of having discrete controls for so many functions is that an expert in using the car can find what they need quickly—like the pilot of a jet aircraft in an emergency. The disadvantage is that a button that turns the heat up will still turn the heat up 3 years from now. It cannot be usefully repurposed; the “user experience” is a fixed one.
My three-year-old Tesla, on the other hand, is still as exciting to me as the day I first got it. Just this morning I noticed a new feature; it’s a trivial one, but cool. When the Tesla is steering itself, there’s a steering wheel icon shown on the dashboard. Just this morning, I noted that the orientation of the steering wheel in the icon follows the orientation of the physical steering wheel—when the car turns left, the icon pivots left. When the car turns right, the icon pivots right. It’s trivial and cosmetic, but given that everything is electronic, it made me think: Is the icon the REAL steering wheel and the physical steering wheel the avatar, or vice-versa? Very Matrix-like.
Empowering the Driver vs. the Car
Could a car be designed that has the self-driving features of the Tesla, and the fine-grained driver-control features of my wife’s new German car? From a technical standpoint, absolutely. However, it’s very interesting that such a car hasn’t been created, at least so far.
I think that’s because of intent and philosophy. A company focused on creating a driver’s car will think about empowering the driver. My Tesla, on the other hand, does not have great driver’s aids like a heads-up display or laser adaptive headlights. I think this is because Tesla’s goal is not to empower the driver—it’s to empower the car to drive itself. The philosophies behind the two approaches are too different for them to merge, at least until one approach or the other becomes commoditized.
I very much look forward to seeing what the next few years will bring to cars. I think we will continue to see progressively more automation migrate into every car. Some cars will continue to appeal to those who like to drive or who distrust technology—but my money is still on the platform approach. I think we’ve just seen the beginning of what a fully-automated, software-controlled, self-driving car can do. That race will be won, I believe, by those who focus on personal transportation as a platform, not as a point solution.
Lotteries are games of chance that appeal to customers from all demographics. State and federal laws have morphed through the years, and digital lottery and casino betting has become more popular as it has become more accessible. For lottery operators and providers, the success of their lottery platform rests on building a safe, certified, and entertaining product.
It’s not an easy task, but the burden can be alleviated by doing three things:
Follow best practices for security and safety
Adopt a lottery app and platform design that incorporates sophisticated lottery app UI and lottery UX
Work with a trusted software engineering partner
Let’s first examine best practices and finish up with a discussion on the importance of finding a trustworthy, experienced software engineering partner.
Security
Developing a safe and secure lottery platform in an age when cybersecurity attacks are at an all-time high is challenging. A recentForbes article compiled a list of “alarming stats,” including the fact that 66% of small to medium-sized businesses (SMBs) have been a target of cyber-attacks within the last 12 months, 40% of SMBs that suffered a severe attack experienced eight hours of downtime, and 83% of SMBs are not financially prepared for the fallout.
Though daunting, becoming a cyber-attack victim is avoidable. There are several best practices that digital lottery and casino gaming developers can implement from the get-go. For example, prior to designing the app and its features, the team should undergo a security assessment. This is something the right software engineering partner can and should provide as part of their services—more on that in a moment. After the evaluation, a secure architecture and design plan must be implemented, along with a secure software development lifecycle (SDLC).
Once building the application commences, it’s crucial to utilize lottery technology—both hardware and software—that provides built-in security features. However, do not assume that generic security features will defeat the advanced machinations of today’s cybercriminals. Security measures should be included at the application level. Consistently testing security protocols and administering staff training is crucial for player protection and the integrity of the application itself.
The World Lottery Association (WLA) agrees, noting on their website, “The security of a lottery will always play a critical role in maintaining the confidence and trust of the public in its lottery games. Therefore, a lottery organization must develop and maintain a visible and documented security environment to achieve and sustain public confidence in its operations.”
Obtaining the WLA Security Control Standard certification (WLA-SCS) further enhances the security of a lottery platform. WLA declares that, for the lottery sector, they are the only internationally recognized security standard. “It is designed to assist WLA members to obtain a level of security control in line with generally accepted best practices and to enable an increased reliance on the integrity of their operations. The WLA-SCS specifies the required practices for an effective security management structure by which a lottery may maintain the integrity, availability, and confidentiality of information vital to its secure operation.”
Lottery App Design
In addition to critical security features for the lottery platform, the lottery app design plays a massive role in its success. Those eager to enter the digital lottery and casino gaming market (forecasted to grow by $220.52 bn during 2020 – 2024) must consider who their customers are and what they want. This is known as the user experience or UX. For a positive lottery UX, the lottery app UI (user interface) must be intuitive, attractive, and ultimately, work correctly (e.g., no log-in problems or missing content) whether the user is on their mobile device or a desktop computer.
A well-designed, user-friendly, personalized lottery platform will engage customers and facilitate an exceptional experience. The experience should include easy log-in, purchasing/withdrawal, and checking result procedures. Additionally, a lottery platform that provides multiple lottery and casino gaming options draws users while also providing further opportunities for increasing lottery platform revenues.
Working with a Software Engineering Partner
Designing a secure and innovative lottery platform requires a specific skill set. The skillset involves understanding how to implement the sophisticated lottery UX, lottery app UI, lottery compliance, and security needed in today’s digital environment. In addition, if lottery operators and providers need agility, speed, and experience to break into the competitive market, they will need to work with a knowledgeable software engineering partner who understands their goals, who can help them innovate in the cloud, and who can integrate seamlessly with their in-house team.
Developing and operating a lottery platform that offers customers a high-value proposition that they can trust is the foundation for success. As a leader in digital product engineering, GlobalLogic and Method (a GlobalLogic company) has been helping clients in the online lottery and betting industry across the globe, and we’d love to do the same for you.
To learn more, visit the Method website or contact our team today. Let’s work together to build something exceptional.
Online sports betting has taken off since the U.S. Supreme Court legalized professional and amateur sports betting in May of 2018. Globally, the most popular sport to bet on is football (soccer to those in the U.S.), making up 70% of the legal—and illegal—wagering, according to Sports Encyclopedia. The NFL receives the second-highest number of bets worldwide, with basketball, tennis, and cricket rounding out the top five. Because of the legal betting surge, sports betting companies have inundated the 58.9bn USD market with consumer-oriented services through the development of feature-rich applications and supporting platforms. In addition, many of these companies embraced a digital product engineering approach to create sophisticated sports betting platforms and software.
Manchester City Football Club
Founded in 1880, Manchester City Football Club (FC), an English football club in Manchester competes in the Premier League, the highest level of English football. They won the Premier League championship in 2018 and all four domestic trophies in England in 2019. The Club wasn’t in the market to facilitate sports betting. Still, they were desirous of improving their online sports fan platform, Cityzens. Unfortunately, the platform garnered lackluster engagement after its debut, and they turned to a partner with Method, - the strategic design arm of GlobalLogic that specialized in digital product engineering for sports & entertainment industry.
Winning with Method
Method is well versed in innovating new products and transforming existing ones. Teaming up with Manchester City FC, they recognized that Cityzens, the first football membership platform focused on digital channels, was an amazing idea that hadn’t come into its own. Research led to the concept of a global fan platform that rewards fans’ loyalty while empowering them with a social tool to create and connect an active, global community. The Manchester City Football Club worked hand-in-hand with Method and GlobalLogic to define, design, build and relaunch the upgraded platform. Our teams at Method and GlobalLogic took a user-centered design approach from the start. As well offered services, including Data Strategy, Experience Design, Product Design, Prototyping, Research & Insights, and Software Engineering.
The platform was relaunch in less than six months and resulted in better understanding of fans’ loyalty and engagement at global scale, reaching approximately 1 million fans worldwide in the first month. The design centered on user experience or UX, but it didn’t forget the analytical needs of Manchester City FC. The admin console provides the Club with the “tools to analyze engagement and behavioral analytics, empowering the club to continually optimize the experience for users—the first football club to do so.”
Success for the Sports Betting Industry
With Manchester City FC, Method and GlobalLogic converted their great idea into a solid, high-performance platform that engages their users and grows their community. We can do the same for sports betting companies and their online sports betting services.
Companies within the sports betting industry, can take advantage of our services (and more) as we partner with them to create, develop, and launch their consumer-oriented services by developing feature-rich applications and betting platforms. (Learn more about this via our recent blog, “5 Things Your Online Gamer is Struggling with Right Now”).
GlobalLogic CEO Shashank Samant says, “We help our clients design and build innovative products, platforms, and digital experiences for the modern world.”
To learn more, visit the Method website or contact us today. Let’s work together to build the exceptional.
After the deregulation of professional and amateur sports betting, media and entertainment (M&E) companies wasted no time creating consumer-oriented services through feature-rich applications and supporting platforms. As a result, digital technologies in sports betting provided avid online gamers enjoyable and secure entertainment—with mixed results.
The market Opportunity
As of October 2021, statistics show that over 30,800 businesses worldwide have entered the sports betting market, which sits at 58.9bn USD and growing. However, growth for sports betting companies may be compromised if they don’t address the expectations of their customers. When their experience with sports betting applications and platforms is abysmal, customers move on to the next one. And they have plenty of other options to choose from.
Online Gamer Expectations
Sports betting companies must assess how their consumer-oriented service may be failing the user. You may currently host an online sports betting application or platform or plan to build one shortly. Either way, you should have insights into current or potential online gamer struggles and identify opportunities to elevate user experience.
Here are five things online gamers and betters are struggling with right now:
Seamless navigation: Poor navigation may be because of a poor UI/UX design interface, introducing friction between the user and the application. Designing an intuitive, user-friendly product using buttons, images, colors, and data directs users where to go and what to do. Customer journey mapping, ethnographic research, design strategy, and superior UI/UX design will significantly eliminate friction and ensure a seamless user experience.
Flexible Options: For instance, laws and regulations may vary from state to state, and sports betting companies must have the technology and platforms to meet the differing requirements. In addition, users must have the option to pay via non-traditional methods like cryptocurrency.
Engaging Content: A betting platform or app should provide timely, relevant, and valuable information about upcoming games, highlights, and statistics. It should outline the features like live streaming, early cash-out, taking control of bets, or betting from the comfort of home. The real value for customers lies in easy access to all kinds of relevant content and connections with the greater sports betting community. They often discuss or share tips on betting, statistics and analysis, and ways to earn freebies.
Anytime. Anywhere Access: Users expect a secure access and seamless experience across games, devices and locations, and throughout the gaming season. Robust platform architecture and rigorous testing mythology will help avoid or minimize the friction due to technical issues like log-in problems, poor latency, crashing apps, or incompatibility across devices.
Broadly focused features: Betting apps designed to engage a wide range of customers may miss the mark due to a lack of personalization. According to independent design publication and blog UX Collective, companies must know their customer: Some numerous personas and journeys exist within the betting world, so make sure to define the journey and the optimal experience for every persona. Too often, we are told that the products and features are for everyone—that’s too broad to create a meaningful and measurable experience.
Overcoming the Challenges with Technology and Innovation
Overcoming industry-specific challenges requires a deep understanding of the application of digital technologies in sports betting and a trusted partner with deep expertise in strategic design, complex engineering, and the sports betting industry. Media & Entertainment companies can bring their vision to life by leveraging the power of ML and AI, Big Data and Analytics, Cloud, DevOps, Mobile/Web technologies to innovate and build next-gen products and platforms, to deliver engaging, data-driven user experiences.
GlobalLogic, a pioneer in digital product engineering, has proven expertise in online gaming/betting and industry-specific platforms. Its Betting Platform Reference Architecture helps clients quickly deploy a platform that can grow with the organization while providing users with an immersive and personalized experience by adding social interaction and gamification to the betting front end. To learn more, click here.
The sports entertainment industry is growing. Live and on-demand sports streaming platforms are being welcomed by sports enthusiasts worldwide.
However, designing and launching a best-in-class streaming product requires access to niche digital skills, which take significant investment, time, and effort. For one of our customers who owns a top-grossing on-demand sports platform, the time and effort were well worth it, but the team didn’t do it alone. The customer and the platform creator (a leading digital sports content and media group) joined forces with Method, a GlobalLogic company, to find worldwide success.
Success: Co-location and Co-creation
A driving force for the customer is to connect the world of sport by producing the most detailed and engaging content. Part of this focus included building a digital product that would disrupt the sports broadcasting industry, making streaming content available to anyone who wanted it. A key member of the client team said, “We have seen a revolution in entertainment with the introduction of disruptive brands like Netflix; now it is sport’s turn to be more consumer-friendly.”
Though the client’s team had a specific vision for its digital product, they still needed help from experts to bring the vision to life. Method – a GlobalLogic company that provides global strategy, UX/UI design, and software engineering was their pick.
Method closely worked with the client’s product development team to build a platform that would reach consumers worldwide. The client worked side-by-side with Method’s product team at their London studio. Co-creation and co-location are two facets of success. Every team member was able to ask questions, make suggestions, and contribute to the overall design in person. This hands-on approach helped teams develop core systems and capabilities and evolve the product in the future.
Varying traditions and cultures affect customer expectations. Before embarking on product design, there was a need to understand the target market. A senior client executive further relayed that “Each of our local products is distinct and specifically intended to drive our business in Japan or our business in Italy.” The client further believed that to get people to subscribe, they must have the content that matters, whether Serie A in Italy, MotoGP in Spain, Bundesliga in Germany, or J-League in Japan, fights in the US, NFL in Canada. You have to build the product around must-have, must-see content.
Method conducted first-hand research, rapid prototyping, and interface concept testing for the initial launch slated for Japan and Germany. It then designed an interface that accommodates a range of formats and interests. Ultimately it’s the content that matters!
The sports app built by Method enabled video-on-demand service accessible via web-enabled devices, including tablets, computers, consoles, or TVs, which viewers in over 200 countries and territories are enjoying today.
Success: Strategic Partnerships
The case study is a resounding example of collaboration and co-creation with clients. Together, we constructed a complex yet adaptive design system with everything the client needed, from interface components and UX guidelines to experience principles. As a result, the app became one of the most profitable sports apps in 2019, and GlobalLogic is proud to have played a considerable part in its global success.
At Method and GlobalLogic, we serve customers across the Media and Entertainment (M&E) segment—especially sports, online gaming, and betting segment—is expanding. GlobalLogic provides consumer-oriented services by developing feature-rich apps and supporting platforms to succeed in a competitive market.
If you’re looking for a strategic partner, choose GlobalLogic. Contact our team today, and let’s work together to build the exceptional.
Operationalization is one of the buzzwords in the technology industry. Even so, it’s still surprising to see operationalization associated with almost all areas of technology such as AnalyticsOps, AppOps, CloudOps, DevOps, DevSecOps, and DataOps.
Although companies rely on their people and data, creating meaningful data is still a challenge for many companies. Obtaining the right data at the right time can bring tremendous value to any company. Today, most organizations focus on collecting insightful data and consolidating their data infrastructure and operations to create a unified structure and data platformization.
This consolidation is the answer to data centralization. All forms of data have a lifecycle and flow through certain steps before the information becomes usable. As a result, we end up designing a highly scalable data platform with the latest and greatest technology, and company operations run smoothly.
Now, we must consider whether using scalable technological processes and implementing an end-to-end data pipeline is the best possible solution out there. There are specific challenges, apart from functional data pipeline development, which can create customer dissatisfaction and a loss in revenue.
These challenges include:
Growing demand for data.
Today, companies rely heavily on data to generate insights to help make decisions. Companies collect various forms of data from numerous different sources. This data impacts business growth and revenue. However, about 80% of that data is unstructured. Companies can use this unstructured or dark data with technology, artificial intelligence, and machine learning methodologies.
The complexity of data pipelines and scarcity of skilled people.
Data comes from multiple sources. The nature of that data is diverse and complex because there are numerous rules and ways to transform that data throughout the pipeline. To address these complexities, companies are looking for skilled data engineers, data architects, and data scientists who can help build these scalable and efficient pipelines. Finding these qualified individuals is a challenge every company faces to backfill demands and create automated processes.
Too many defects.
Even after rigorous quality checks, the complexity of these data pipelines creates a system full of defects that are then released to production. Once production reports the defects, it takes time to analyze and fix the issue, leading to SLA misses and customer dissatisfaction.
Speed and accuracy of data analytics.
Every company wants efficient and accurate analytics. However, when teams work in silos, it becomes challenging to create effective data pipelines. This is because quality collaboration among operations and data teams must take place to help identify requirements accurately before implementation.
Companies pretty much universally aim to deliver fast, reliable, and cost-effective products to customers while generating revenue. Accurate and reliable data is the force behind this goal, and DataOps is the methodology to build a data ecosystem to help industries capitalize on revenue streams.
What is DataOps?
Gartner’s Definition
“DataOps is a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and data consumers across an organization”.
In other words, the goal of DataOps is to optimize the development and execution of the data pipeline. Therefore, DataOps focuses on continuous improvement.
Dimensions of DataOps
DataOps is not an exact science as it works against different dimensions to overcome developmental challenges. However, when DataOps operates on a high level, it can be factored into the following dimensions:
Agile:
Short sprints
Self-organized teams
Regular retrospection
Keep customer engaged
Total Quality Management:
Continuous monitoring
Continuous improvement
DevOps:
TDD approach
CI/CD implementation
Version Control
Maximize automation
In looking at the different components, it’s clear we need competent teams to implement these dimensions. To create the DataOps processes, we require technical teams of data engineers, data scientists, and data analysts. These teams must collaborate and inegrate their plans with business teams of data stewards, CDOs, product owners, and admins who help define, operate, monitor, and deploy the components that keep business processes running.
Addressing Challenges and Data Monetization Using DataOps
Figure One
In the data platform, the data lifecycle goes through multiple steps. Figure One shows that data comes from different data sources: structured and unstructured data, video, and text. After processing data through the batch or streaming engine, it transforms into meaningful information stored in the data lake or polyglot storage. Then, stored significant data publishes through the consumer layer for the downstream or consuming system.
In this data flow, we usually focus on collecting data while keeping business objectives in mind and we create clean, structured data from transactional systems or warehouses. Generally, companies require this data from the consumer. Still, several questions remain:
Are we reaping any actual benefits from the required data?
Are data quality issues reported at the right time?
Do we have an efficient system that points out problematic areas?
Are we using the right technology to help monitor and report our system issues effectively?
So how do we address the challenges mentioned above to use the correct information at the right time through DataOps?
To explain this, we’ll use the following example.
Example: Identifying defects in earlier phases of development helps companies monetize their data.
We develop data pipelines focused on business functionality by utilizing the latest cutting-edge technology. When the teams deliver the final product to production, multiple defects arise. When the system reports defects, it takes a significant amount of time to analyze and fix the problems. By the time the teams resolve the problems, the SLAs are over. In many cases, these pipelines are critical and have specific SLAs and constraints.
Figure Two
I’ve worked with multiple companies to design their data pipelines. When I distribute data pointers on five maturity models, it appears as pictured in Figure Two.
However, most companies are only at maturity level one or two, where issues are either detected from production or it takes a lot of time to fix those identified issues. In addition, very few companies have matured processes in which they proactively determine issues or create automated RCAs with a self-healing mechanism. Through DataOps processes and methodology, companies can achieve higher maturity levels.
We must add a highly collaborative data and operations team that works in tandem to set the goals and optimize proper processes, technologies, and methodologies to mature our data pipeline. This collaborative process helps to proactively identify slow or problematic data, automatically reports root cause analysis, and operates with self-healing systems. Today, companies rely heavily on artificial intelligence and machine learning technology to automate their bug reporting and for a self-healing system. These systems expedite the overall process to achieve defined SLAs and gain customer satisfaction.
Summary
DataOps is a combination of processes and technologies that automates quality data delivery to improve data value according to business objectives and requirements. It can fasten the data cycle timeline, generate fewer data defects, greater code reuse, and accelerate business operations by creating more efficient and agile processes with timely data insights.
DataOps can increase overall performance through high output, quality, and productivity in SLAs. Proper DataOps processes, governance teams, and technology can help industries capitalize on revenue streams, as well. Today, data is one of the most valuable resources there is, and it is the force for any company’s growth potential.
Data is the key to understanding behavior, patterns, and insights. Without data, it is incredibly complicated to gain the knowledge to decide the right actions to meet objectives. Therefore, collecting the right data is a crucial aspect of a data and analytics platform. But recent events show that the way organizations collect customer data and customer usage data for web applications will change.
Google announced that it will block cross-site tracking through third-party cookies by the end of 2023. This change means that using third parties to collect data will no longer be possible. With other browsers such as Safari and Firefox also working towards phasing out third-party cookies on their browser, the end of third-party cookies is here.
With privacy laws like GDPR coming into effect in recent years, how organizations can collect and use data is subject to many regulations. The privacy laws have also ensured that data privacy is at the forefront of the users’ thoughts, with notices for data usage requiring user consent. However, obtaining third-party data usage consent has become problematic because users are reluctant to share data when presented with information on its use.
Now that third-party data is more difficult to acquire, first-party data has become essential and needs to be a priority in an organization’s data strategy. But, first, let’s define the difference between first-party and third-party data before further discussing the situation.
The organization itself collects first-party data, and it has exclusive ownership of the data. However, external entities typically collect third-party data and then aggregate it for sale to different parties. Utilizing first-party data means more than just collecting data directly from consumers and customers. It also means first-party data needs to be secured and managed correctly with appropriate governance to ensure transparency and privacy across the whole data lifecycle.
Now, we’ll discuss the main pillars of an effective first-party data strategy to harness first-party data.
First-Party Data Strategy Pillars
Collection
First, organizations must decide what data to collect based on business objectives and user experience goals. The next step is to collect this data from users. Since there is friction getting consent for user’s data, earning the user’s trust through appropriate data collection channels is crucial.
For example, utilizing loyalty benefits or offers can help gain the user’s trust. It is also essential to provide full transparency on how the organization will use the data since users don’t want to receive irrelevant advertising.
Organizations also need to invest in new technology, applications, and websites to collect first-party data with user consent and move away from third-party mechanisms. However, organizations can retain the ownership of data and analysis, and strategic partnerships can develop technological modules. Additionally, customer data platforms can help solve the technical puzzle of collecting first-party data.
Consent
It is essential to get consent from users to secure the use of the data. Organizations need to ensure transparency on how the data will be used and obtain an agreement from users or customers. Additionally, organizations need to adhere to the customer agreement to process and use the data and comply with laws and regulations.
Governance
Data governance means understanding the policies, processes, and structures applied to support data security, compliance, storage, management, data classification and data usage. Implementing the right data governance processes to ensure compliance with laws, regulations, and user consent is crucial to maintain the customers’ trust regarding their privacy and avoid potentially heavy fines.
Identity Resolution
Organizations must create customer profiles with appropriate data anonymization standards to protect the customer’s identity. Data stewardship and data governance practices can also help uphold the agreement with the customer. Additionally, organizations can tie customer profiles to channels and device-level identifiers to ensure there’s no violation of data collected from different channels. These processes are also crucial in case customers no longer want to share their data with the organization.
Data Platform
Organizations need a data platform to collect, store, analyze and process first-party data from different sources that can also provide analytical models. Additionally, the data platform should include modern data warehouses and custom data tools.
Data Use
The way organizations use first-party data is crucial. Obtaining user consent and adhering to the agreement builds trust not just with the user but also with customers. Additionally, the users are more likely to continue providing data as they see its value to the organization they built trust with over time.
First-Party Data Strategy with GlobalLogic
At GlobalLogic, we advise our partners on data strategy and implementation of data platforms, modern data warehouses, and data governance processes. These services can help lay the foundation for first-party data strategy and usage. If you’re ready for the transition from third-party to first-party data collection, please reach out to the Big Data & Analytics department at GlobalLogic to discuss data advisory and data platform implementation. In addition, we can help create the data governance processes and show you how to manage first-party data with relevant monetization applications.
There are numerous opportunities for CSPs to integrate 5G and its capabilities into a platform to capitalize on advantageous revenue streams. When creating an innovative and connected platform, there are many components to consider, such as a distributed cloud infrastructure, industry-specific services, and more. Additionally, there are unique challenges to overcome and plan for, such as high investment costs and security concerns.
Only through partnering with subject matter experts on a developer platform can CSPs maximize the investment they made in 5G to take full advantage of B2B and B2B2X opportunities. Learn about the ways to overcome potential risks through specific collaboration opportunities and an integrated developer platform to profit from potential revenue streams.
Children’s Aspirations and Education in the Pandemic World
One of the most profound implications of COVID-19 was the impact on 1.5 billion children worldwide -- and the disruption to their traditional in-classroom education. For those who were lucky enough to have access to the bandwidth, computers and technology, this meant entirely different ways of learning and education, and for the many who didn’t have access, this meant a catastrophic interruption to their education. So what have children really missed out on?
Dr. Ger Graus will enlighten us about new ways of looking at educating children, beyond the traditional systems and structures of schooling. You will get an entirely new perspective of how to inspire children to think about who they want to be (vs. defining themselves by an occupation).
About Dr. Ger Graus
Professor Dr Ger Graus OBE is a renowned figure in the field of education. He was the first Global Director of Education at KidZania, and, prior to that, the founding CEO of the Children’s University. In 2019, Ger was invited to become a Visiting Professor at the National Research University in Moscow, Russia. In 1983 he moved to the United Kingdom where he began his teaching career and subsequently became an Education Adviser, a Senior Inspector, and Director of Education.
Ger is a member of the Bett Global Education Council, Junior Achievement’s Worldwide Global Council, chairs the Beaconhouse School System’s Advisory Board, Pakistan, Advises the Fondazione Reggio Children, Italy, and has been invited by His Highness Sheikh Hamadan Bin Mohammed Al Maktoum, Crown Price of Dubai, to help shape the future of education in Dubai as a member of the Dubai Future Councils. He also works with and advises organizations globally on the learning agenda in its widest sense, including the Organization for Economic Co-operation and Development (OECD), WISE as part of the Qatar Foundation, the UK Information Commissioner’s Office, as well as the business world.
In the 2014 Queen’s Birthday Honor’s List Ger was made an Honorary Officer of the Most Excellent Order of the British Empire (OBE) for services to children. In his book ‘Natural Born Learners’, author Alex Beard says: “In learning terms, Ger Graus is Jean-Jacques Rousseau meets Willy Wonka.”
